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Studies on a-amylase and ethanol production from spoiled starch rich vegetables and multi objective optimization by P.S.O and Genetic Algorithm

Authors: S. B. Rajulapati; M. Lakshmi Narasu;

Studies on a-amylase and ethanol production from spoiled starch rich vegetables and multi objective optimization by P.S.O and Genetic Algorithm

Abstract

India is the second major vegetable producer in the world. But due its nature and composition majority of the vegetables are prone to spoile. A large quantity of spoiled starch and cellulose rich vegetables waste is thrown away into the environment. That leads to both air and soil pollution. Vegetables are rich in starch and celluloses. In this regard, experiments were conducted to convert these carbohydrates to ethanol. Simultaneous saccharification and fermentation was performed with different bacteria and fungi cultures, which are isolated from local vegetable market. Yield of the ethanol depends on the amount of glucose present in the medium. Glucose level depends on α-amylase activity and the amount of enzyme produced. So optimization of amylase production plays crucial role in the process. This process was optimized by two level five factorial (Time, PH, Temperature, Starch Concentration, Inoculum size) central composite design using Design-Expert 7.0. In order to increase glucose concentration both the activity and amount of enzyme need to be optimized. So multi objective optimization was carried out by Particle Swarm optimization (P.S.O) and Genetic Algorithm (G.A) using MATLAB R2009a. Saccharification process was finished at optimized values. Then the alcohol fermentation was carried with Zymomonas mobilis on Enzyme (from Aspergilus Niger) mediated saccharified substrate, it was found to be 12.1 mg/ml of alcohol was obtained.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
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